class_docstr: Create PNG plots of samples from a GAN model.
  
  Arguments:
      filename (string): Filename prefix for output PNGs.
      hw (int): Height and width of the images.
      nchan (int): number of channels.
      num_saples (int): how many samples to show from traning and generated data.
      sym_range (bool): pixel value [-1, 1] or [0, 1].
      padding (int): number of pixels to pad in output images.
      plot_width (int): width of output images.
      plot_height (int): height of output images.
      dpi (float): dots per inch.
      font_size (int): font size of labels.
      epoch_freq (int): number of epochs per plotting callback.
code: def _value_transform(self, batch):
      if self.nchan == 1:
          batch = 1.0 - batch
      else:
          if self.sym_range:
              batch = (batch + 1.0) / 2.0
      return batch
  
file_path: neon/neon/callbacks/plotting_callbacks.py
imports: from __future__ import division
  import logging
  import numpy
  from PIL import Image
  from neon.callbacks.callbacks import Callback
label_desc: Use image node_id 2 for calling the GANPlotCallback obj's underlying member method code with example usage: obj._value_transform(batch) and returns: batch